Open AccessImproving Grapevine Sustainability through Multifactorial Machine Learning Application
Author(s) -
Francisco José Lacueva Pérez,
Sergio Ilarri Artigas,
Rafael del Hoyo,
Juan José Barriuso
Publication year - 2020
Publication title -
jornada de jóvenes investigadores del i3a
Language(s) - English
Resource type - Journals
ISSN - 2341-4790
DOI - 10.26754/jjii3a.4868
Subject(s) - phytosanitary certification , sustainability , adaptation (eye) , sustainable development , phenology , risk analysis (engineering) , business , computer science , economics , biology , ecology , economic growth , neuroscience
Wine farms have to adapt their activities to achieve sustainable development goals. Our goal is to contribute to this adaptation by developing Machine Learning models to predict phenology and pest risk with the aim of reducing applied phytosanitary treatments.